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      Pyrosequencing-based comparative genome analysis of the nosocomial pathogen Enterococcus faecium and identification of a large transferable pathogenicity island

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          Abstract

          Background

          The Gram-positive bacterium Enterococcus faecium is an important cause of nosocomial infections in immunocompromized patients.

          Results

          We present a pyrosequencing-based comparative genome analysis of seven E. faecium strains that were isolated from various sources. In the genomes of clinical isolates several antibiotic resistance genes were identified, including the vanA transposon that confers resistance to vancomycin in two strains. A functional comparison between E. faecium and the related opportunistic pathogen E. faecalis based on differences in the presence of protein families, revealed divergence in plant carbohydrate metabolic pathways and oxidative stress defense mechanisms. The E. faecium pan-genome was estimated to be essentially unlimited in size, indicating that E. faecium can efficiently acquire and incorporate exogenous DNA in its gene pool. One of the most prominent sources of genomic diversity consists of bacteriophages that have integrated in the genome. The CRISPR-Cas system, which contributes to immunity against bacteriophage infection in prokaryotes, is not present in the sequenced strains. Three sequenced isolates carry the esp gene, which is involved in urinary tract infections and biofilm formation. The esp gene is located on a large pathogenicity island (PAI), which is between 64 and 104 kb in size. Conjugation experiments showed that the entire esp PAI can be transferred horizontally and inserts in a site-specific manner.

          Conclusions

          Genes involved in environmental persistence, colonization and virulence can easily be aquired by E. faecium. This will make the development of successful treatment strategies targeted against this organism a challenge for years to come.

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          Most cited references85

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          Profile hidden Markov models.

          S. Eddy (1998)
          The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
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            Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome".

            The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for approximately 80% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.
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              CRISPR interference limits horizontal gene transfer in staphylococci by targeting DNA.

              Horizontal gene transfer (HGT) in bacteria and archaea occurs through phage transduction, transformation, or conjugation, and the latter is particularly important for the spread of antibiotic resistance. Clustered, regularly interspaced, short palindromic repeat (CRISPR) loci confer sequence-directed immunity against phages. A clinical isolate of Staphylococcus epidermidis harbors a CRISPR spacer that matches the nickase gene present in nearly all staphylococcal conjugative plasmids. Here we show that CRISPR interference prevents conjugation and plasmid transformation in S. epidermidis. Insertion of a self-splicing intron into nickase blocks interference despite the reconstitution of the target sequence in the spliced mRNA, which indicates that the interference machinery targets DNA directly. We conclude that CRISPR loci counteract multiple routes of HGT and can limit the spread of antibiotic resistance in pathogenic bacteria.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2010
                14 April 2010
                : 11
                : 239
                Affiliations
                [1 ]Department of Medical Microbiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
                [2 ]Institute for Genome Sciences, Department of Microbiology and Immunology, University of Maryland School of Medicine, BioPark II Room 629, 801 West Baltimore Street, Baltimore, MD 21201, USA
                [3 ]Department of Biology, Faculty of Science, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
                [4 ]Hubrecht Institute for Developmental Biology and Stem Cell Research, Cancer Genomics Center, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands
                [5 ]Department of Microbiology, University of Chicago, Chicago, USA
                Article
                1471-2164-11-239
                10.1186/1471-2164-11-239
                2858755
                20398277
                29e8cd42-f9b6-4a79-a32f-c2a10aa8e638
                Copyright ©2010 van Schaik et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 December 2009
                : 14 April 2010
                Categories
                Research Article

                Genetics
                Genetics

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